key: cord-0705708-dgiwgkm1 authors: Yang, Mi; He, Manxi; Gao, Shan title: Infection-control practices in the COVID-19 pandemic call for an evidence-based management system in psychiatric hospitals date: 2020-08-29 journal: Asian J Psychiatr DOI: 10.1016/j.ajp.2020.102403 sha: fdc96d9319b99f20901aea14a5973325085a6e98 doc_id: 705708 cord_uid: dgiwgkm1 nan Please cite this article as: Yang M, He M, Gao S, Infection-control practices in the COVID-19 pandemic call for an evidence-based management system in psychiatric hospitals, Asian Journal of Psychiatry (2020), doi: https://doi.org/10. 1016/j.ajp.2020.102403 This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Psychiatric hospitals generally have a small and specialized supply of drugs, materials, equipment, and facilities, and also specialized allocation of human resources, compared with comprehensive medical institutions. Therefore, when they are faced with the outbreak of a major respiratory infectious disease like the novel coronavirus disease 2019 (COVID-19), the investment and stock of human resources and material resources such as non-psychiatric drugs, common disinfectants, and personal protective equipment are particularly insufficient, which increases the risks of nosocomial infection. The characteristics of psychiatry hospitals and their real experience in infection control during the COVID-19 pandemic point to the necessity to initiate a responsive and effective infection control system against outbreaks of major respiratory infectious diseases including COVID-19, which may reemerge as a chronic epidemic similar to influenza (Yang and Jin, 2020) . On the one hand, it is necessary to establish and regularize an integrated management framework based on official guidelines and professional experience, which includes several component systems of different functions as follows. • To specify the definition and characteristics of major respiratory infectious diseases that activate the hospital infection control system (Gan et al., 2014) may be used to obtain eigenvectors of personnel quantity, material demand, and fund allocation, which will be taken as input features of the neural network. Support vector machines (Steinwart and Christmann, 2008) may be utilized to alter the dimension of eigenvectors and convolutional neural networks J o u r n a l P r e -p r o o f following feature training. In short, it is a future direction to combine professional experience with data modeling and machine learning to develop a highly effective and responsive system for hospitals to control infections of major respiratory infectious diseases. We need learn from the data in the COVID pandemic to facilitate future policy decision-making in context of psychiatric hospital management in order to protect our patients and healthcare workers (Tandon, 2020) . There are No conflict of interest. Nil. Compressive sensing using chaotic sequence based on Chebyshev map ImageNet classification with deep convolutional neural networks Support Vector Machines COVID-19 and mental health: Preserving humanity, maintaining sanity, and promoting health An acute respiratory infection runs into the most common noncommunicable epidemic-COVID-19 and cardiovascular diseases Prevention and control of COVID-19 infection in a Chinese mental health center This study was supported by the National Natural Science